Large-scale head-to-head comparison of on- and off-target profiles of [18F]Tauvid and [18F]MK6240 tau-PET in aging and Alzheimer’s disease

Background Tau-PET imaging enables in vivo quantification of neurofibrillary tangles, but tracers such as [ 18 F]Tauvid and [ 18 F]MK6240 present distinct affinities and off-target binding properties. Using the multicenter HEAD research cohort, a large-scale study designed to characterize the aging and Alzheimer’s disease (AD) spectrum, this study directly compares tracer performance to support harmonization across cohorts and clinical trials. Methods 681 participants underwent MRI, amyloid-β (Aβ)-PET, and tau-PET scans with both [ 18 F]Tauvid and [ 18 F]MK6240. We analyzed regions reflecting AD-related tau deposition (on-target) and known age-related or off-target binding. Analyses included paired t-tests, linear regressions, effect sizes and correlation matrices between the two tracers, across on-target and off-target regions. We further assessed tracer signal separation quantifying the noise to dynamic range ratio (NRR), where lower values indicate better assessment of tau. Results Tracers showed strong correlations in on-target regions (R = 0.81–0.95 in the whole cohort; R = 0.83–0.95 in Aβ+; R = 0.59–0.71 in Aβ-), supporting robust tau pathology detection. While off-target regions also correlated (R = 0.58–0.74 in the whole cohort; R = 0.55–0.80 in Aβ+; R = 0.57–0.73 in Aβ-), retention magnitudes differed: [ 18 F]Tauvid presented higher retention in the white matter, basal ganglia and choroid plexus, while [ 18 F]MK6240 had higher retention in the meninges and extracortical region near the entorhinal cortex. Voxelwise paired t-tests and NRR analyses, conducted at both ROI and voxelwise levels, demonstrated that [ 18 F]MK6240 consistently yielded lower NRR values across the cortex, indicating better signal separation, and potentially greater sensitivity for detecting early tau accumulation. Conclusion [ 18 F]Tauvid and [ 18 F]MK6240 capture largely overlapping patterns of tau pathology, but differ notably in the magnitude of off-target binding. These findings highlight the importance of understanding tracer similarities and differences to guide tracer selection and to improve harmonization across studies. Independent and tracer-specific optimizations of pipelines are essential before harmonization across tracers can be achieved, thereby facilitating accurate cross-study comparisons and improving clinical translation.